Our team builds computational and experimental tools for engineering the properties of inorganic materials through synthesis design and control of atomic-scale transformations.
Using DFT and Monte Carlo methods to understand how atomic rearrangements underpin materials functionality.
Shedding light on materials synthesis by using high-temperature X-ray diffraction to monitor reactions in real time.
Developing foundation models to accelerate simulations and automate the analysis of experimental data.
We introduce GALAXI, a scalable framework that combines phase-specific classifiers with Rietveld refinement to identify multiphase mixtures from powder X-ray diffraction.
Undergraduate researcher Ethan Jin has been awarded a place in the UCLA Samueli Summer Undergraduate Research Program (SURP).
Members of the group traveled to Honolulu for the 2026 MRS Spring Meeting, where Prof. Szymanski gave a tutorial on machine learning and AI for materials characterization.